ABSTRACT

Context The average age of registered nurses (RNs), the largest group of health
care professionals in the United States, increased substantially from 1983
to 1998. No empirically based analysis of the causes and implications of this
aging workforce exists.

Objectives To identify and assess key sources of changes in the age distribution
and total supply of RNs and to project the future age distribution and total
RN workforce up to the year 2020.

Design and Setting Retrospective cohort analysis of employment trends of recent RN cohorts
over their lifetimes based on US Bureau of the Census Current Population Surveys
between 1973 and 1998. Recent workforce trends were used to forecast long-term
age and employment of RNs.

Participants Employed RNs aged 23 to 64 years (N = 60,386).

Main Outcome Measures Annual full-time equivalent employment of RNs in total and by single
year of age.

Results The average age of working RNs increased by 4.5 years between 1983 and
1998. The number of full-time equivalent RNs observed in recent cohorts has
been approximately 35% lower than that observed at similar ages for cohorts
that entered the labor market 20 years earlier. Over the next 2 decades, this
trend will lead to a further aging of the RN workforce because the largest
cohorts of RNs will be between age 50 and 69 years. Within the next 10 years,
the average age of RNs is forecast to be 45.4 years, an increase of 3.5 years
over the current age, with more than 40% of the RN workforce expected to be
older than 50 years. The total number of full-time equivalent RNs per capita
is forecast to peak around the year 2007 and decline steadily thereafter as
the largest cohorts of RNs retire. By the year 2020, the RN workforce is forecast
to be roughly the same size as it is today, declining nearly 20% below projected
RN workforce requirements.

Conclusions The primary factor that has led to the aging of the RN workforce appears
to be the decline in younger women choosing nursing as a career during the
last 2 decades. Unless this trend is reversed, the RN workforce will continue
to age, and eventually shrink, and will not meet projected long-term workforce
requirements.

Figures in this Article

Registered nurses (RNs) comprise the largest group of health care professionals
in the United States, with more than 2.0 million RNs employed in health care
organizations in 1998.1 This profession has
experienced substantial changes during the last decade.2- 8
However, little attention has been given to the change in the age structure
of the RN workforce. Data from the Census Current Population Survey (CPS)
show that between 1983 and 1998 the average age of working RNs increased by
more than 4 years, from age 37.4 to 41.9 years.1
During the same time period, the proportion of the RN workforce younger than
30 years decreased from 30.3% to 12.1%, and the actual number of working nurses
younger than 30 years decreased by 41%. In hospitals, the average age of RNs
increased by 5.3 years between 1983 and 1998.9
In contrast, the average age of the US workforce as a whole increased by less
than 2 years during this period (age 37.4 to 39.0 years), while the total
labor force in the United States younger than 30 years decreased by less than
1%.

Explanations for the increasing average age of RNs involve a combination
of demographic, social, and educational forces. Although the proportion of
men in nursing has been increasing, explanations focus on women, who continue
to make up more than 90% of the RN workforce. The size of the cohort of women
aged 15 to 19 years from which nurse education programs drew students during
the 1960s and 1970s declined in the 1980s, thereby decreasing the number of
younger prospective nursing students in the US population. Also, the recent
expansion of career opportunities and rising wages for women relative to men10 may have further reduced the pool of prospective
nursing students because many women entered other careers. Similar aging trends
have occurred in other professions and occupations traditionally dominated
by women (eg, teachers, social workers, secretaries, and hair dressers). In
addition, the aging of the RN workforce has been attributed to the expansion
of 2-year associate degree nursing programs during the 1980s, which apparently
attracted individuals in their mid to late 30s interested in a second career.11 Currently, 59% of entry-level nursing students graduate
from associate-degree programs (Theresa M. Valiga, RN, EdD, National League
for Nursing, 2000, unpublished data for 1998).

The nursing profession has been increasingly concerned about the ramifications
of its aging workforce. In a survey of health care executives in 1995, the
aging of the RN workforce was among the most frequently identified problems.12 In 1996, the Institute of Medicine noted that older
RNs have a reduced capacity to perform certain physical tasks and warned that
the aging of the workforce presents serious implications for the future.13 A 1999 survey administered to nurse executives during
a national conference found that 83% believed that the aging of the RN workforce
will result in serious shortages of RNs in the next 10 to 15 years (P.I.B.,
unpublished data, 1999).

Despite this concern within the nursing profession, there has been little
empirically based analysis of the causes and implications of an aging RN workforce.
In this article, we investigate the quantitative contribution of various factors
to the aging of the RN workforce. Using annual data from the past 25 years,
we analyze the employment patterns of successive cohorts of RNs during their
lifetimes to identify and assess key sources of observed changes in the age
distribution and total supply of RNs, project the future age distribution
and total RN supply to the year 2020, and compare projections to estimated
requirements for RNs over the same period.

METHODS

Data

Data on employment of RNs were obtained from the CPS, which is a household-based
survey administered monthly by the Bureau of the Census that covers a nationally
representative sample of more than 100,000 individuals.1
In addition to demographic information collected in each month of the survey,
detailed questions about employment (including occupation and hours worked)
have been asked since 1973. Between 1973 and 1978, these questions were asked
of all respondents to the May survey. From 1979 through 1998 (the latest year
for which complete data were available), 25% of the sample in every month
was asked the employment questions. The sample in each year was a representative
cross-section of individuals, but each housing unit appears in the sample
twice (exactly 1 year apart). Thus, some individuals may appear twice in the
sample. Data from the CPS are used extensively by researchers and by the US
Department of Labor to estimate current trends in unemployment, employment,
and earnings.

Data from the CPS were obtained for all individuals aged 23 to 64 years
employed as RNs in the week of the survey (N=60,386). Because individuals
aged 65 years and older comprise less than 2% of the RN workforce, they were
excluded from the analysis. Registered nurses who worked less than 30 hours
in a typical week were considered part-time workers. These data were used
to estimate the number of RNs of each single year of age who were working
in each year. We estimated the number of working RNs on a full-time equivalent
(FTE) basis (ie, as the number of full-time employees plus one-half the number
of part-time employees). All estimates were weighted by sampling weights provided
by the CPS, making them representative of the US noninstitutionalized population.

To ensure confidence that estimates based on CPS data reflect the population
of RNs in the United States, CPS estimates were compared with data reported
in the National Sample Survey of Registered Nurses (NSSRN).14
This survey, conducted by the Bureau of Health Professions approximately every
4 years since the late 1970s, is the principal source of national data on
RNs. As shown in Table 1, CPS
estimates of the average age and total number of RNs are similar to NSSRN
estimates from corresponding years. Beginning in 1984, the NSSRN changed from
asking age (as is done in the CPS) to asking year of birth, and the difference
in the survey question appears to have generated a slight increase in the
average age estimated by the NSSRN as compared with CPS. For our analysis,
we relied solely on the CPS data because the CPS is available annually and
has asked a consistent set of questions over a longer time period than the
NSSRN.

Additional data on the US population by year and age between 1970 and
1998 were obtained from US Bureau of the Census.15
Forecasts of the US population through 2020 by age were obtained from the
"middle series" projections prepared by the US Bureau of the Census.16

Statistical Analysis

Model. The analysis relies on a simple statistical model, commonly used by
demographers and economists, that decomposes observed changes in the size
and age of the RN workforce over time into 3 distinct components: population,
cohort, and age effects.17 The term population refers to the size of the total US population of a given
age in a given year. Population effects are expected to play an important
role because the overall age distribution in the United States has changed
recently with the aging of the baby boom generation. The term cohort refers to all the individuals born in any given year. Likewise,
the term cohort effect refers to the propensity of
individuals born in any given year to work as RNs. Cohort effects are expected
to be important because women born in recent years have much broader career
opportunities and, therefore, are less likely to choose nursing over other
professions. Finally, the term age refers to a person's
age in a given year. Age effects reflect the relative propensity of RNs to
work at any given age and are expected to capture the tendency of RNs to work
less during their childbearing years and as they approach retirement age.

More formally, the number of FTE RNs of a given age (a) that were born
in a given year (b) can be described by the following equation:

a,ba,bba

The observed cohorts, born between 1909 and 1975, correspond to the
cohorts that were between age 23 and 64 years at some point in the CPS sample
years (1973-1998). The first term on the right-hand side of equation 1 captures
population effects, with POPULATIONa,b referring to the total US
population of a given birth cohort (b) at a given age (a). The second term
captures cohort effects, with qb representing the propensity of
individuals from a given cohort to work as RNs. The final term captures age
effects, with αa representing the relative propensity of
RNs to work at a given age. Thus, the total number of FTE RNs of a given age
that are working in a given year is the product of the size of the population,
the propensity of that cohort to choose nursing as a career, and the propensity
of RNs to be working at that age.

Estimation. Both the cohort effects (qb) and the age effects (αa) are parameters that must be estimated. Rearranging Equation 1 and
taking logs yields the following estimation equation:

a,ba,bba

Analysis of variance (ANOVA) was used to estimate the parameters of
this equation. The unit of observation was an age-cohort group (eg, the 1955
cohort at age 30 years). The dependent variable was the logged fraction of
a given birth cohort at a given age that is working as RNs (defined on an
FTE basis). The data cover 42 age years (23-64 years) and 26 calendar years
(1973-1998) for a total of 1092 observations. The ANOVA model estimated main
effects for cohort (birth year) and age. These parameter estimates were exponentiated
to yield estimates of qb and αa. Standard errors
for these estimates were calculated by the bootstrap method in a manner that
accounted for the existence of multiple observations in the sample for some
individuals and households.18

It is important to note that the ANOVA model in Equation 2 does not
include main effects for the year in which the RNs were working (ie, year
effects). If year effects were included, then age and cohort effects would
no longer be uniquely identified because year, cohort (or birth year), and
age are linearly related to each other (year=birth year+age).17
Thus, in the context of our model, a major change to conditions facing the
entire RN workforce in a given year may be manifested via the cohort effect
for future cohorts but not via a uniform effect on RNs of all ages working
in a given year. For example, a sudden jump in RN wages may make nursing more
attractive to new cohorts of RNs entering the labor market but would not encourage
older cohorts to work more. This assumption is supported by findings from
many studies showing that variation in RN wages has small effects on labor
supply,19- 21 suggesting
that year effects are likely to be small and may be safely ignored. In addition,
year effects were not found to be jointly statistically significant at the
5% level (P=.08) when added to the model.

Forecasting. Forecasts of the total number of FTE RNs of each age in the years 2000-2020
were constructed based on Equation 1. The FTE forecasts were summed by year
and age to produce aggregate forecasts. Constructing forecasts for a given
age group in a given year required estimates of the population by age in future
years, along with estimates of the cohort (qb) and age (αa) effects for the age group in that year. Population estimates were
obtained from the US Census "middle series" projections. The ANOVA model in
Equation 2 provides estimates of age effects (αa) for each
age (23-64 years). The model also provides estimates of cohort effects (qb) for cohorts born between 1909 and 1975. However, the model does not
provide estimates of cohort effects for cohorts that were born after 1975
(not yet age 23 years by 1998, the last year of our data). Therefore, to construct
forecasts of the cohort effect (qb) for cohorts born after 1975,
we used the average cohort effect from the 5 most recent cohorts observed
in the estimation period (the cohorts born from 1971-1975). If future cohorts
behave like recent cohorts, then this will yield accurate forecasts. We also
investigated the sensitivity of forecasts to this assumption. Standard errors
on the forecasts were estimated using the bootstrap method in a manner that
accounted for the existence of multiple observations for some individuals
and households.18

RESULTS

Estimates of Age and Cohort Effects

Estimates of age effects (αa) from the model described
in Equation 2 were jointly statistically significant (P<.001). Figure 1A plots
the estimates relative to the effect at age 45 years (ie, αa/α45). Thus, if population and cohort are fixed, Figure 1A shows the expected size of the RN workforce at each age
as a percentage of the size of the workforce at age 45 years.

Figure 1. Estimated Percentages of RN FTEs
by Age and Year

RN indicates registered nurse; FTEs; full-time equivalents. Estimates
are based on the model described in Equation 2, "Statistical Analysis" subsection.
Figure 1A shows expected percentage of RN FTEs for a given cohort at each
age relative to age 45 years (open circles). Standard errors for these estimates
are 5%-10%. Figure 1B shows RN FTEs at age 45 years relative to 1955 birth
cohort at age 45 years (in 2000) by population effect (open circles), cohort
effect (open triangles), and total FTEs (closed squares). Standard errors
are 5%-8% for estimates between 1978 and 2011 and 5%-15% for all other estimates.

The overall pattern of the age effects is consistent with expectations
of how work effort varies over the life cycle. There is at first a rapid,
and then more gradual, rise in FTEs through age 45 years, as many RNs finish
nursing education and enter the labor force while others increase labor force
activity as they pass out of their child-rearing years. Total FTEs are relatively
stable from approximately age 45 to 55 years, followed by a rapid decline
as RNs approach the usual retirement age of 65 years. Note that the age effects
reflect both the number of RNs in the labor force at any given age and the
average hours worked among those RNs in the labor force. Thus, while average
hours worked among RNs in the labor force generally peaks prior to age 40
years,21 total FTEs peak somewhat later because
of an increased number of RNs in the labor force at older ages.

Estimates of cohort effects (qb) from the model were jointly
statistically significant (P<.001). Figure 1B plots the estimates relative to the cohort of individuals
born in 1955—or equivalently, relative to the cohort that is age 45
years in the year 2000. The estimates are reported according to the year in
which each cohort turned age 45 years (rather than the cohort's birth year). Figure 1B also shows estimates of the relative
cohort effects (qb/q1955) and relative population effects
(Populationb/Population1955). In addition, we plot the
product of these 2 effects, which is an estimate of the size of the RN workforce
at a given age, relative to the 1955 birth cohort at the same age (total FTEs,
age 45 years). Thus, Figure 1B shows
the estimated size of the RN workforce that was or will be aged 45 years in
each year, relative to the year 2000, and how much of the relative difference
is due to population vs cohort effects.

The estimated differences across years are dramatic and consistent with
expectations of how population and the attractiveness of a nursing career
have changed over time. We estimate that the number of 45-year-old RNs will
peak around the year 2000, reflecting both the effects of the baby boom (ie,
a large overall population aged 45 years) and the high propensity of women
born around 1955 to choose nursing as a career (ie, a large cohort effect).
Prior to 1990, there were less than half as many 45-year-old RNs because of
both a smaller overall population aged 45 years and a lower propensity of
these earlier cohorts to choose nursing as a career. However, after the year
2000, most of the estimated decline in 45-year-old RNs will be due to the
lower propensity of cohorts born after 1955 to choose nursing as a career
(cohort effects). For example, in 2015 there will be about as many individuals
aged 45 years in the population as there are in the year 2000, but the number
of 45-year-old RNs will be about 35% lower because the cohort born in 1970
was much less likely to choose nursing as a career than the cohort born in
1955.

Evaluating the Validity of the Model

One criterion for evaluating the validity of our approach is the model's
ability to predict the size and age distribution of the RN workforce within
the estimation sample. The overall fit for the model was relatively good,
with an adjusted R2 of 0.82. The model's ability to fit the data is apparent in Figure 2, which plots the predicted and actual number of FTE RNs
for selected 5-year birth cohorts. Each data point represents an average over
5 birth-year cohorts. For example, the curve marked "1945-1949" traces out
the predicted average annual FTEs supplied by RNs born in 1945-1949 at age
28 through 49 years. The actual number of average annual FTEs supplied by
RNs in these cohorts lies quite close to the predicted values. Moreover, as
predicted by the model, each cohort appears to follow a similar trajectory
of FTE production as the cohort ages. Yet while the curves follow roughly
the same shape with age, each cohort tends to provides a different level of
FTEs throughout its lifetime. This is best illustrated by the 1955-1959 cohort,
which has supplied more FTEs at every age than other cohorts.

Figure 2. Predicted and Actual Number of FTE
RNs by Age for Selected 5-Year Birth Cohorts

The implications of Figure 2
for the size of the future RN workforce are profound. The number of FTE RNs
supplied by the largest cohorts (eg, 1955-1959) are likely to remain stable
for another 10 to 15 years, before declining as these cohorts reach retirement
age. However, the number of RNs supplied by younger cohorts (eg, 1965-1969)
are likely to remain well below the number supplied by cohorts born in the
1950s. Thus, in the short term we can expect an aging workforce (as the largest
cohorts grow older), while in the longer term the workforce will shrink (as
the largest cohorts retire and are replaced by much smaller cohorts of RNs).

To evaluate the model's ability to forecast RN supply beyond the estimation
sample, we conducted a split-sample forecast. The model was estimated using
data from 1973-1988 only, and the results were then used to forecast FTE RN
supply for the years 1989-1998 (see "Methods" section for details). We show
the results in Figure 3 aggregated
in 2 ways: the upper curve shows total annual RN FTEs of all birth cohorts
and ages and the lower curves show a similar comparison of forecasts for RNs
younger than 40 years and for RNs aged 40 years and older. The forecast from
our model tracks the actual number of FTEs quite well. In contrast, a Health
Resources and Services Administration (HRSA) projection, based on data from
1988, underpredicted the number of FTEs throughout the 1990s, with a mean
squared error more than 5 times as large as that for the forecast from our
model.22 In addition, our model accurately
forecast a decline in the number of RNs younger than 40 years (and an accelerating
growth aged 40 years and older) despite the fact that there was little evidence
of this trend prior to 1988. Overall, the split-sample forecasts support the
validity of our model: the model correctly predicted both the continued growth
in FTEs, and the changeover in predominance from younger to older RNs that
occurred in the 1990s.

Figure 3. Split-Sample Forecast of Total Annual
RN FTEs and FTEs for RNs Younger Than 40 Years and Age 40 Years and Older

The upper curve (shown in squares) is the total annual full-time
equivalents (FTEs) produced by registered nurses (RNs) of all birth cohorts
and ages in a given year. In lower curves (shown in triangles and circles),
the FTEs are split into those produced by RNs aged 40 years and older and
younger than 40 years. Closed symbols represent forecast for the years 1989
through 1998. Projections made by the Health Resources and Services Administration
(HRSA) in 1988 of total FTE RN supply for the years 1990-1998 are provided
for comparison.22

Projection to 2020

Using the same methods as in the split-sample forecast, we estimated
the model by using all years of data (1973-1998) and projected the size of
the RN workforce for the years 2001-2020. These projections, along with 90%
confidence intervals, are shown in Figure
4. Our projections suggest that, following years of steady growth,
the overall number of FTE RNs per capita will reach a peak in the year 2007
and will thereafter decline for the remainder of the forecast period. The
absolute size of the RN workforce (not per capita) begins declining in 2012,
and by 2020 will be approximately the same size as it is today. Based on these
projections, the size of the RN workforce will be near HRSA-estimated requirements
during the first decade of the new millennium, but will fall nearly 20% below
requirements by the year 2020.

For comparison, the most recent (1995) estimates of RN requirements
made by HRSA are plotted.23 The HRSA estimates
are based on models of demand in each major employment sector that take into
account changes in demographic variables, health insurance coverage, income
and affluence levels, and the impact of managed care. Error bars represent
90% confidence intervals. FTEs indicates full-time equivalents.

In addition to a decline in overall labor supply, the projections indicate
a continued aging of the RN workforce. Figure
5 shows the actual and projected age distribution of the RN workforce
every 10 years from 1980-2020. After increasing by roughly 3 years between
1990 and 2000, the average age of working RNs is projected to increase another
3 years before peaking at age 45.4 years in 2010 and declining slowly thereafter.
Here again, the large 1950s cohorts dominate past and future trends in RN
labor supply. In 1980 and 1990, when these large cohorts were in their 20s
and 30s, the RN workforce was dominated by young RNs, with more than half
the workforce younger than 40 years. By the year 2000, however, this distribution
changes substantially. The 1950s cohorts are in their 40s, and RNs of this
age dominate the workforce, outnumbering RNs in their 20s by nearly 4 to 1
(compared with 1980, when RNs in their 20s actually outnumbered RNs in their
40s). By 2010, the age distribution will have shifted as far as it will go
(just before the 1950s RNs begin to retire), and more than 40% of RNs are
projected to be older than 50 years. Only when the 1950s cohorts are reaching
retirement age in 2020 does the projected distribution begin to shift back
toward younger RNs.

Figure 5. Actual and Projected Number of RN
FTEs by Age Group for Selected Years

Forecast Assumptions

These forecasts depend importantly on 2 assumptions. First, we have
assumed that future cohorts will enter nursing at a rate similar to cohorts
that are currently in their mid 20s. Of course, future cohorts could be more
likely to enter nursing (eg, if wages or work conditions improve) or less
likely to enter nursing (eg, if the trend toward better career opportunities
for women in other occupations continues). If we assumed that all future cohorts
would be 10% more (less) likely to enter nursing, then the model would forecast
an RN workforce in 2020 that was roughly 4.5% larger (smaller) and half a
year younger (older). Thus, while the magnitude of the projected aging and
future shortage is somewhat sensitive to what we assume about future cohorts,
our basic conclusions are not. For example, for there to be no shortage by
the year 2020, we would have to assume that all future cohorts (beginning
with the cohort entering the labor market this year) entered nursing at a
rate similar to that seen among the cohorts born in the 1950s. In other words,
the size of the RN workforce during the next 20 years is largely determined
by the size of cohorts that have already entered the labor market, and changes
in the size of entering RN cohorts will be felt only gradually.

A second important assumption of our model is that changes over time
in the size of the workforce for any given cohort depend only on the age of
the cohort, and not factors that are specific to a given year. Thus, for a
given cohort, any increase in the number of FTEs over time is interpreted
as an age effect and not the result of economy-wide factors such as increasing
wages. Of course, some of the increase in FTEs seen over the 1980s may have
been in part caused by rising wages. We investigated this possibility by estimating
alternative models that incorporated these year effects in various ways (results
available from authors). These alternative models yielded estimates of age
effects that increased less with age. The resulting forecasts of total FTEs
were roughly similar in shape but 10% lower by 2020. Forecasts based on these
alternative models were not robust to small changes in specification but consistently
imply a workforce that is aging and shrinking even more rapidly than indicated
by our base analysis.

COMMENT

Our analysis suggests that a fundamental shift occurred in the RN workforce
during the last 2 decades. As opportunities for women outside of nursing have
expanded, the number of young women entering the RN workforce has declined.
This decline in the propensity of younger cohorts to choose nursing as a career
has resulted in a steadily aging RN workforce. Over the next decade this aging
will continue as the largest cohorts of RNs will be in their 50s and 60s,
after which the RN workforce will contract as these cohorts begin to retire.
As a result, the size of the RN workforce is forecast to be nearly 20% below
projected requirements by 2020.

The continued aging of the RN workforce has important implications for
employers. Efforts to restructure patient care delivery must be more ergonomically
sensitive to older RNs, who are more susceptible to neck, back, and feet injuries
and have a reduced capacity to perform certain physical tasks compared with
younger RNs who once dominated the workplace.24
Also, older and more experienced RNs may have higher expectations of working
conditions and require greater autonomy and respect than has typically been
accorded.

The RN shortages we foresee are in stark contrast to the oversupply
expected by the Pew Health Professions Commission in 1995.25
Moreover, unlike past shortages, the coming RN shortage will be driven by
fundamental, permanent shifts in the labor market that are unlikely to reverse
in the next few years. As shortages develop during the next 20 years, it can
be expected that RN wages will rise, and employers will have little choice
but to substitute other personnel for RNs. In anticipation of these developments,
employers and nursing leaders should begin working together now to plan how
best to use increasingly scarce RNs to deliver patient care in the future.

Long-term strategies to increase RN supply are needed to avoid a shortage.
Although higher wages and better working conditions may attract more women
and men to choose nursing as a career, these effects will occur only slowly
and will be limited by the continued expansion of career opportunities for
women outside of nursing. Alternatively, immigration of RNs educated outside
the United States may provide the most feasible strategy. However, eliminating
the projected shortage would require immigration on an unprecedented scale,
and such a policy would not be without controversy.

Finally, the impending decline in the supply of RNs will come at a time
when the first of 78 million baby boomers begin to retire and enroll in the
Medicare program in 2010. Because RNs are vital in ensuring access to and
quality of health care, it is critical that policymakers understand, and develop
appropriate responses to, the implications of a rapidly aging RN workforce.

Population Division of the Census Bureau. Population Projections of the United States by Age,
Sex, Race, and Hispanic Origin: 1995 to 2050 [machine-readable data
file]. Washington, DC: US Bureau of the Census; May 1996.

Pew Health Professions Commission. Critical Challenges: Revitalizing the Health Professions
for the Twenty-first Century. San Francisco: University of California, San Francisco, Center for
the Health Professions; 1995.

Figures

Figure 1. Estimated Percentages of RN FTEs
by Age and Year

RN indicates registered nurse; FTEs; full-time equivalents. Estimates
are based on the model described in Equation 2, "Statistical Analysis" subsection.
Figure 1A shows expected percentage of RN FTEs for a given cohort at each
age relative to age 45 years (open circles). Standard errors for these estimates
are 5%-10%. Figure 1B shows RN FTEs at age 45 years relative to 1955 birth
cohort at age 45 years (in 2000) by population effect (open circles), cohort
effect (open triangles), and total FTEs (closed squares). Standard errors
are 5%-8% for estimates between 1978 and 2011 and 5%-15% for all other estimates.

Figure 2. Predicted and Actual Number of FTE
RNs by Age for Selected 5-Year Birth Cohorts

Figure 3. Split-Sample Forecast of Total Annual
RN FTEs and FTEs for RNs Younger Than 40 Years and Age 40 Years and Older

The upper curve (shown in squares) is the total annual full-time
equivalents (FTEs) produced by registered nurses (RNs) of all birth cohorts
and ages in a given year. In lower curves (shown in triangles and circles),
the FTEs are split into those produced by RNs aged 40 years and older and
younger than 40 years. Closed symbols represent forecast for the years 1989
through 1998. Projections made by the Health Resources and Services Administration
(HRSA) in 1988 of total FTE RN supply for the years 1990-1998 are provided
for comparison.22

For comparison, the most recent (1995) estimates of RN requirements
made by HRSA are plotted.23 The HRSA estimates
are based on models of demand in each major employment sector that take into
account changes in demographic variables, health insurance coverage, income
and affluence levels, and the impact of managed care. Error bars represent
90% confidence intervals. FTEs indicates full-time equivalents.

Figure 5. Actual and Projected Number of RN
FTEs by Age Group for Selected Years

Population Division of the Census Bureau. Population Projections of the United States by Age,
Sex, Race, and Hispanic Origin: 1995 to 2050 [machine-readable data
file]. Washington, DC: US Bureau of the Census; May 1996.

Pew Health Professions Commission. Critical Challenges: Revitalizing the Health Professions
for the Twenty-first Century. San Francisco: University of California, San Francisco, Center for
the Health Professions; 1995.

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